Before a Code Division Multiple Access ("CDMA") cellular network can be implemented, an RF ("radio-frequency") plan or model must be developed regarding the cell-site location. RF planning requires configuring the cell-site placement such that optimum cellular-customer service levels are achieved while minimizing the network infrastructure costs. The configuration requires consideration of numerous CDMA network parameters, such as cellular demand, technology restrictions, and site restrictions. Examples of cellular demand is the estimated cellular traffic distribution of the area; of technology restrictions are cellular base station signal power levels, antenna characteristics, and antenna height; and of site restrictions is site costs (typically easement expenses or rents) and land-use restrictions imposed by local, state, and federal governments (e.g., height restrictions, aesthetic looks, etc.).
The cost for a cell-site installation is very expensive, being estimated at hundreds of thousands of dollars. Although this exorbitant cost is commonplace, inefficient planning techniques nevertheless continue to be used for CDMA network cell-site planning.
An example of such network cell-site planning techniques is to first apply a two-dimensional grid to an installation area, each grid section representing a cell-site. With the grid in place, then the CDMA network parameters such as cellular demand, technology restrictions, and site restrictions are considered for removing cell sites from the grid. Next, the intuition and experience of the engineer is applied to make a final assessment regarding the service coverage adequacy of the network cell-site plan.
Then, to determine the potential cell-site set suitability, physical cell tests are conducted in the form of (1) drive tests and (2) site visits. Drive tests are used to calibrate the radio-frequency propagation models used in the RF plan. Site visits are used to perform radio-frequency suitability analysis. After the time and effort are spent to develop the RF plan, then further computer programs have been used to optimize to refine and to improve the signal propagation model accuracy.
Due to heavy reliance on the judgment and expertise of the plan designer, the conventional method above has several disadvantages. First, a beginning RF-plan designer requires costly and time-consuming training and education, both in book knowledge and practical experience, before being able to develop RF plans. Second, because the level of proficiency of designers can fluctuate, inconsistent RF plans over a given network result. Third, the time and expense an employer has spent on training a designer can come to naught as the designer makes a career move, leaving a gap in critical personnel. Fourth, the resulting design, although perhaps suitable for providing the cellular service needed, is lacks efficient use of communications equipment. That is, the same communications coverage could be had with less equipment.
Furthermore, such RF planning methods have not considered "cell breathing"--coverage fluctuations in that the cell coverage area decreases due to the power drain caused by cellular traffic increases. Also, the sheer number of cell sites for a given network area can create complexities that overwhelm traditional planning methods, resulting in much less than maximized cell site optimization. Often, the result under conventional RF planning techniques is a less-than-optimal cell placement acquired at an extraordinary design cost.
As a further difficulty, the interference between cells is difficult to assess when there is not even an existing network design. The location and size of neighboring cells has not been determined, which makes the task of calculating other-cell interference difficult. Therefore, before the network has been designed, the other-cell interferences must be estimated. Also, the "other-cell interference factor," or "f-factor," must be estimated. The f-factor is defined as the ratio of the total interference caused by a mobile cellular in other cells over the total interference caused by the mobile cellular in the present cell.
Thus, a method for cell-site placement optimization that is simplified over the conventional design practice is highly sought. Further, it is also sought that such optimization systems could be applied to either new cellular coverage areas or to existing cellular coverage areas. Such a system would be used with minimal instruction.